AI+ Developer™
# AT-310
Master AI Development: From Fundamentals to Advanced Tools
Certification Duration:
40hrs
The AI+ Developer™ certification provides a comprehensive learning path into core AI development concepts. Designed for aspiring developers, this program covers key areas like Python programming, data processing, deep learning, and algorithm optimization. Participants will gain hands-on experience in Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning, enabling them to solve real-world challenges effectively. The curriculum includes advanced modules on time series analysis, model explainability, and cloud-based deployment strategies. Upon completion, learners will hold the expertise to tackle complex AI system design and deployment, making them industry-ready.
Self-paced Online Course Access:
Get instant access to the entire E-learning material.
₱15,960.00
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
- Core AI Foundations: Covers Python, deep learning, data processing, and algorithm design
- Hands-on Projects: Focus on NLP, computer vision, and reinforcement learning
- Advanced Modules: Includes time series, model explainability, and cloud deployment
- Industry-Ready Skills: Prepares learners to design and deploy complex AI systems
Python Programming Proficiency
Students will gain a solid foundation in Python programming, a crucial skill for implementing AI algorithms, processing data, and building AI applications effectively.
Deep Learning Techniques
Learners will master machine learning and deep learning techniques to address challenges in classification, regression, image recognition, and natural language processing.
Cloud Computing in AI Development
Students will get hands-on experience in cloud-based AI application development and learn how to use AWS, Azure, and Google Cloud for scalable AI systems.
Project Management in AI
Participations will master the skills necessary to manage AI projects effectively, from initiation to completion, including planning, resource allocation, risk management, and stakeholder communication.
GitHub Copilot
Lobe
H20.ai
Snorkel
- Basic math, including familiarity with high school-level algebra and basic statistics, is desirable.
- Understanding basic programming concepts such as variables, functions, loops, and data structures like lists and dictionaries is essential.
- A fundamental knowledge of programming skills is required.
Certification Overview
- Course Introduction
Module 1: Foundations of Artificial Intelligence
1.1 Introduction to AI
1.2 Types of Artificial Intelligence
1.3 Branches of Artificial Intelligence
1.4 Applications and Business Use Cases
Module 2: Mathematical Concepts for AI
2.1 Linear Algebra
2.2 Calculus
2.3 Probability and Statistics
2.4 Discrete Mathematics
Module 3: Python for Developer
3.1 Python Fundamentals
3.2 Python Libraries
Module 4: Mastering Machine Learning
4.1 Introduction to Machine Learning
4.2 Supervised Machine Learning Algorithms
4.3 Unsupervised Machine Learning Algorithms
4.4 Model Evaluation and Selection
Module 5: Deep Learning
5.1 Neural Networks
5.2 Improving Model Performance
5.3 Hands-on: Evaluating and Optimizing AI Models
Module 6: Computer Vision
6.1 Image Processing Basics
6.2 Object Detection
6.3 Image Segmentation
6.4 Generative Adversarial Networks (GANs)
Module 7: Natural Language Processing
7.1 Text Preprocessing and Representation
7.2 Text Classification
7.3 Named Entity Recognition (NER)
7.4 Question Answering (QA)
Module 8: Reinforcement Learning
8.1 Introduction to Reinforcement Learning
8.2 Q-Learning and Deep Q-Networks (DQNs)
8.3 Policy Gradient Methods
Module 9: Cloud Computing in AI Development
9.1 Cloud Computing for AI
9.2 Cloud-Based Machine Learning Services
Module 10: Large Language Models
10.1 Understanding LLMs
10.2 Text Generation and Translation
10.3 Question Answering and Knowledge Extraction
Module 11: Cutting-Edge AI Research
11.1 Neuro-Symbolic AI
11.2 Explainable AI (XAI)
11.3 Federated Learning
11.4 Meta-Learning and Few-Shot Learning
Module 12: AI Communication and Documentation
12.1 Communicating AI Projects
12.2 Documenting AI Systems
12.3 Ethical Considerations
Optional Module: AI Agents for Developers
1. Understanding AI Agents
2. Case Studies
3. Hands-On Practice with AI Agents
What will I gain from completing this certification?
Upon completion, you will receive an AI+ Developer™ certification, showcasing your proficiency in AI. You’ll have the skills to tackle real-world AI challenges and implement advanced AI solutions in various domains.
Do I need any prior AI knowledge to join this course?
While prior AI knowledge is not mandatory, a fundamental understanding of Python programming and basic math and statistics will help you grasp the advanced concepts covered in this course.
Are there any hands-on projects in the course?
Yes, the course includes various hands-on projects and practical exercises to help you apply theoretical concepts to real-world scenarios, reinforcing your learning through practical experience.
Can I choose a specialization during the course?
You cannot choose a specialization in this course. However, you will be trained in areas such as Natural Language Processing (NLP), computer vision, and reinforcement learning.
How will my progress be evaluated?
Your progress will be evaluated through a combination of quizzes, hands-on exercises, and a final assessment. These evaluations are designed to test your understanding and application of the material.